Current noisy intermediate-scale quantum (NISQ) computers [1]} open up a new route to tackle a variety of computational problems that cannot be addressed efficiently with classical computers. Potential applications range from machine learning [2]} to finance [3]} to various optimization problems [4]}, [5]}. In particular, quantum computers intrinsically evade the sign problem that hinders Monte Carlo simulations of strongly correlated quantum-many body problems in certain parameter regimes [6]}. While current hardware is still of limited size and suffers from a considerable level of noise, it has already been successfully demonstrated that NISQ devices can outperform classical computers [7]}. Moreover, techniques for mitigating the effects of noise are rapidly developing [8]}, [9]}, [10]}, [11]}, [12]}.
